Read the text and give it a suitable title.

The web creates new challenges for information retrieval. The amount of information on the web is growing rapidly, as well as the number of new users inexperienced in the art of web research. People are likely to surf the web using its link graph, often starting with high quality human maintained indices such as Yahoo! or with search engines. Human maintained lists cover popular topics effectively but are subjective, expensive to build and maintain, slow to improve, and cannot cover all esoteric topics. Automated search engines that rely on keyword matching usually return too many low quality matches. To make matters worse, some advertisers attempt to gain people's attention by taking measures meant to mislead automated search engines. We have built a large-scale search engine which addresses many of the problems of existing systems. It makes especially heavy use of the additional structure present in hypertext to provide much higher quality search results. We chose our system name Google, because it is a common spelling of googol, or 10¹⁰⁰ and fits well with our goal of building very large-scale search engines.

Search engine technology has had to scale dramatically to keep up with the growth of the web. In 1994, one of the first web search engines, the World Wide Web Worm (WWWW) had an index of 110,000 web pages and web accessible documents.

As of November, 1997, the top search engines claim to index from 2 million to 100

million web documents. At the same time, the number of queries search engines handle has grown incredibly too. In March and April 1994, the World Wide Web Worm received an average of about 1,500 queries per day. In November 1997 Altavista claimed it handled roughly 20 million queries per day. The goal of our system is to address many of the problems, both in quality and scalability, introduced by scaling search engine technology to such extraordinary numbers.

Creating a search engine which scales even to today's web presents many challenges. Fast crawling technology is needed to gather the web documents and keep them up to date. Storage space must be used efficiently to store indices and, optionally, the documents themselves. The indexing system must process hundreds of gigabytes of data efficiently. Queries must be handled quickly, at a rate of hundreds to thousands per second.

These tasks are becoming increasingly difficult as the Web grows. However, hardware performance and cost have improved dramatically to partially offset the difficulty. There are, however, several notable exceptions to this progress such as disk seek time and operating system robustness. In designing Google, we have considered both the rate of growth of the Web and technological changes. Google is designed to scale well to extremely large data sets. It makes efficient use of storage space to store the index. Its data structures are optimized for fast and efficient access.

Further, we expect that the cost to index and store text or HTML, will eventually decline relative to the amount that will be available. This will result in favorable scaling properties for centralized systems like Google.

Сеть создает новые проблемы для информационного поиска. Количество информации в сети растет быстро, также как и число новых пользователей, неопытных в искусстве веб-исследования. Люди, вероятно, будут бродить по сети, используя его график ссылки, часто начиная с высококачественных, поддерживаемых указателей и, такие как Yahoo! или с поисковыми системами. Поддерживаемые списки затрагивают популярные темы эффективно, но субъективны, дороги в создании и обслуживании, медленные в обновлении, и не может затронуть все тайные темы. Автоматизированные поисковые системы, которые полагаются на ключевое слово, обычно выдают слишком много низкокачественных соответствий. Чтобы усугубить положение, некоторые рекламодатели пытаются привлечь внимание людей, принимая меры, предназначенные, чтобы ввести в заблуждение автоматизированные поисковые системы. Мы создали крупномасштабную поисковую систему, которая рассматривает многие проблемы существующих систем. Это делает особенно интенсивное использование дополнительной структуры, существующих в гипертексте, чтобы обеспечить наиболее высокие качественные результаты поиска. Мы выбрали наш Google имени системы, потому что это - общее написание googol, или 10100 и соответствует хорошо нашей цели создания очень крупномасштабных поисковых систем.

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